Code for KHGT model, AAAI2021

Overview

KHGT

Code for KHGT accepted by AAAI2021

Please unzip the data files in Datasets/ first.

To run KHGT on Yelp data, use

python labcode_yelp.py

For MovieLens data, use the following command to train

python labcode_ml10m.py --data ml10m --graphSampleN 1000 --save_path XXX

and use this command to test with larger sampled sub-graphs

python labcode_ml10m.py --data ml10m --graphSampleN 5000 --epoch 0 --load_model XXX

For Online Retail data, use this command to train

python labcode_retail.py --data retail --graphSampleN 15000 --reg 1e-1 --save_path XXX

and also load the model to test it with larger sampled sub-graphs

python labcode_retail.py --data retail --graphSampleN 30000 --epoch 0 --load_model XXX
Comments
  • Issue run retail dataset

    Issue run retail dataset

    Hi, Thank you for your quick response. I was unable to run the code on retail dataset. (and Successfully run the code on ml10m and yelp datasets ) BTW, I have fixed the following minor issues to enable the correctness:

    • change the folder name from 'Yelp' to 'yelp' (match the folder name in DataHandler_time.py)
    • change line 14 in DataHandler_time.py to 'retail' (instead of 'Tmall')

    During the execution of

    python labcode_retail.py --data retail --graphSampleN 15000 --reg 1e-1 --save_path model_name
    

    The error pops out due to the index out of range. I think these are some issues with the dataset. Please let me know if you could get it run. And would you mind to sharing me the original data and data preprocessing code?

    opened by KylinA1 3
  • The axis of softmax supposed to be 0?

    The axis of softmax supposed to be 0?

    def GAT(self, srcEmbeds, tgtEmbeds, tgtNodes, maxNum, Qs, Ks, Vs):
    	QWeight = tf.nn.softmax(NNs.defineRandomNameParam([args.memosize, 1, 1], reg=True), axis=1)
    	KWeight = tf.nn.softmax(NNs.defineRandomNameParam([args.memosize, 1, 1], reg=True), axis=1)
    	VWeight = tf.nn.softmax(NNs.defineRandomNameParam([args.memosize, 1, 1], reg=True), axis=1)
    	Q = tf.reduce_sum(Qs * QWeight, axis=0)
    	K = tf.reduce_sum(Ks * KWeight, axis=0)
    	V = tf.reduce_sum(Vs * VWeight, axis=0)
    

    I found above code to implement equation (3), I have 2 questions:

    1. I think it should be below:
    tf.nn.softmax(..., axis = 0) 
    
    1. For all behavior $k$, there supposed to be only 1 group of $Q^h_m, m = 1\cdots, M$ to aggregated from, according to equation (3). While in practical implementation, each behavior $k$ has its own $M$ channels basis parameters.

    Please excuse me if there is any misunderstanding.

    opened by KylinA1 1
  • Datasets problem

    Datasets problem

    Dear author, I would like to ask you some problems in datasets that is, the user of each dataset exceed 10000, but I found that only 10000 users in test data For example, there are 67788 users in ML10M, but only 10000 users are chosen for test, is it reasonable? Thanks!

    opened by Weile0409 1
  • embedding of uEmbed0/iEmbed0 and UEmbedPred/IEmbedPred

    embedding of uEmbed0/iEmbed0 and UEmbedPred/IEmbedPred

    Hello I have a question about embedding of uEmbed0/iEmbed0 and UEmbedPred/IEmbedPred.

    In "ours" function, why Embed0 is replaced by a random initialized EmbedPred in code line 125~126 in labcode_ml10m.py?I didn't find a description of it in the paper, and I don't understand what the motivation is for doing so.

    I am confused.

    Anyway, thanks of the codes. It is pretty.

    opened by fsgdrq 1
  • embedding of srcNodes and tgtNodes

    embedding of srcNodes and tgtNodes

    Hello, I have a question. In the "messagePropagate" function, why do srcNodes and tgtNodes look up their embeddings in the same embedding table?

    opened by GhostShipZ 1
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